7 citations · 8 across the 7 of their papers we have counts for
7 papers
MapReduce LoRA: Advancing the Pareto Front in Multi-Preference Optimization for Generative Models
Chieh-Yun Chen, Zhonghao Wang, Qi Chen +10
Reinforcement learning from human feedback (RLHF) with reward models has advanced alignment of generative models to human aesthetic and perceptual preferences. However, jointly opt…
HALO: Human-Aligned End-to-end Image Retargeting with Layered Transformations
Yiran Xu, Siqi Xie, Zhuofang Li +13
Image retargeting aims to change the aspect-ratio of an image while maintaining its content and structure with less visual artifacts. Existing methods still generate many artifacts…
MALT Diffusion: Memory-Augmented Latent Transformers for Any-Length Video Generation
Sihyun Yu, Meera Hahn, Dan Kondratyuk +6
Diffusion models are successful for synthesizing high-quality videos but are limited to generating short clips (e.g., 2-10 seconds). Synthesizing sustained footage (e.g. over minut…
Calibrated Multi-Preference Optimization for Aligning Diffusion Models
Kyungmin Lee, Xiaohang Li, Qifei Wang +7
Aligning text-to-image (T2I) diffusion models with preference optimization is valuable for human-annotated datasets, but the heavy cost of manual data collection limits scalability…
AfriMed-QA: A Pan-African, Multi-Specialty, Medical Question-Answering Benchmark Dataset
Tobi Olatunji, Charles Nimo, Abraham Owodunni +23
Recent advancements in large language model(LLM) performance on medical multiple choice question (MCQ) benchmarks have stimulated interest from healthcare providers and patients gl…
Cropper: Vision-Language Model for Image Cropping through In-Context Learning
Seung Hyun Lee, Jijun Jiang, Yiran Xu +10
The goal of image cropping is to identify visually appealing crops in an image. Conventional methods are trained on specific datasets and fail to adapt to new requirements. Recent…
Parrot: Pareto-optimal Multi-Reward Reinforcement Learning Framework for Text-to-Image Generation
Seung Hyun Lee, Yinxiao Li, Junjie Ke +11
Recent works have demonstrated that using reinforcement learning (RL) with multiple quality rewards can improve the quality of generated images in text-to-image (T2I) generation. H…